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Parallel architecture and optimization for discrete-event simulation of spike neural networks 被引量:5

Parallel architecture and optimization for discrete-event simulation of spike neural networks
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摘要 Spike neural networks are inspired by animal brains,and outperform traditional neural networks on complicated tasks.However,spike neural networks are usually used on a large scale,and they cannot be computed on commercial,off-the-shelf computers.A parallel architecture is proposed and developed for discrete-event simulations of spike neural networks.Furthermore,mechanisms for both parallelism degree estimation and dynamic load balance are emphasized with theoretical and computational analysis.Simulation results show the effectiveness of the proposed parallelized spike neural network system and its corresponding support components.
出处 《Science China(Technological Sciences)》 SCIE EI CAS 2013年第2期509-517,共9页 中国科学(技术科学英文版)
基金 supported by the National Natural Science Foundation of China (Grant Nos. 61003082,60921062,61005077)
关键词 spike neural network discrete event simulation intelligent parallelization framework 神经网络系统 并行体系结构 离散事件仿真 优化 离散事件模拟 平衡机制 动态负载 仿真结果
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